Vehicle Trajectory Control via Real-Time Gain Adaptation
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Solution Overview
Problem
Existing vehicle trajectory control systems face challenges in maintaining robustness and efficiency, particularly in adapting to varying vehicle speeds and road grip conditions, leading to potential lane departure accidents due to inadequate handling of disturbances.
Innovation Solution
A vehicle trajectory control device that generates a stabilizing action setpoint by multiplying a state vector by a gain, with a gain production module adapted in real-time to vehicle speed and state vector, minimizing trajectory deviations through linearization and convex optimization, ensuring minimal lateral overshoot and stability across varying conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a braking force is applied to control yaw movement and return the vehicle to the center of the lane, then the vehicle can be controlled back to the lane, but the vehicle experiences energy loss due to deceleration
Solution Approach 1:
The patent replaces the mechanical braking system with an electric motor system for trajectory correction. The motor applies torque to the drive wheels to generate yaw moment, substituting the passive braking mechanism with an active propulsion-based control system that avoids energy loss from deceleration.
Solution Approach 2:
The patent changes the control parameter from braking force to motor torque. By adjusting the torque applied to the drive wheels, the system achieves yaw control without the energy dissipation inherent in braking, transforming the control mechanism from friction-based to electromagnetic-based.
2Adaptability or versatility
If electric power steering or differential braking is used for active assistance, then the vehicle can be steered back to the lane, but the system does not adequately account for vehicle speed and road grip variations
Solution Approach 1:
The patent implements a dynamic control system that continuously adapts to changing vehicle conditions. The motor torque is calculated based on real-time parameters including vehicle speed and estimated road grip, allowing the system to adjust its response dynamically rather than using fixed control parameters.
Solution Approach 2:
The system employs feedback control by continuously monitoring vehicle state (position, speed, yaw rate) and adjusting the motor torque accordingly. The control algorithm incorporates vehicle speed and road grip estimation to modify the control action, ensuring reliable performance across varying conditions.
3Reliability
If automated active trajectory-maintaining functions are implemented, then lane departure can be prevented, but the system lacks robustness in varied situations
Solution Approach 1:
The patent achieves robustness through parameter adaptation. The control system modifies key parameters including motor torque magnitude, vehicle speed weighting, and road grip estimation based on actual operating conditions. This allows the same basic control structure to perform reliably across diverse situations from dry to wet roads and varying speeds.
Data Source
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AI summary
In order to control the trajectory of a vehicle (1), the device (40) comprises a module (50) for developing, in real time, a stabilising action set value (?f*) applicable to the vehicle, by multiplying a state vector Formula (I) of the vehicle by a gain (K) at each sampling point, and a module (48) for producing the gain (K) adapted, in real time, to a speed range containing the speed (v) of the vehicle (1) and to the state vector, by minimising a sum of at least two squares of the trajectory variations Formula (II) deduced from the state vector.